Engineering at Anthropic Scaling Managed Agents: Decoupling the brain from the hands Get started with Claude Managed Agents by following our docs . A running topic on the Engineering Blog is how to build effective agents and design harnesses for long-running work . …
… But the security and reliability of agents cannot be achieved by any single company working alone. Across the ecosystem, the question is how to create the conditions in which enterprises can experiment with agents and developers can keep building safely. …
… We need collective investment in agent-specific security posture, from shared benchmarks and disclosure norms to common identity standards and cross-vendor red-teaming. We focus on containment in this piece, but that's only one part of the security picture for agents. …
… Claude's Agent SDK has unlocked a step-change in how we operate—converting rigid research processes into adaptive, compliant agents. …
… In addition, NEC is already integrating Claude into its Security Operations Center services to help defend customers against increasingly sophisticated cybersecurity threats. Claude will also be integrated into the next-generation cybersecurity service NEC is currently providing. …
… 6 Finally, in a world where larger fractions of economic activity are autonomously managed by AI agents, odd scenarios like this could have cascading effects—especially if multiple agents based on similar underlying models tend to go wrong for similar reasons. …
… Security work that took hours now takes minutes. …
… With Claude Cowork and Managed Agents embedded inside it, KPMG professionals and their clients can build new AI capabilities directly in the platform—work that used to mean jumping between tools, chat windows, and weeks of effort. “Building an AI agent to help clients adjust to changing tax regulat… …
… We are enabling clients to scale AI with confidence—built on robust governance, security, and trust by design. …
… Claude Opus 4.5 represents a breakthrough in self-improving AI agents . For automation of office tasks, our agents were able to autonomously refine their own capabilities—achieving peak performance in 4 iterations while other models couldn’t match that quality after 10. …